Knowing the total weight of a vehicle (i.e. the vehicle's own weight and, if present, the weight of load) is of great interest in many automotive applications. Many control decisions and diagnosis systems can be improved if this parameter can be estimated accurately. For example, an indirect tire pressure monitoring system uses the wheel rolling radius as an indicator of low tire pressure. Since the rolling radius is correlated to the vehicle mass, knowledge of the load in the vehicle is of great importance.
U.S. Pat. No. 5,973,273 discloses to mount, as additional sensors, vertical accelerometers on the vehicle and to look for changes in the vertical displacement's frequency behavior of the vehicle. Here, the need for additional sensors results is a drawback, which also does not allow using this approach in existing vehicles without modification.
US 2002/0038193 A1 discloses to estimate the load of a heavy truck based on information on pressure of an air-suspension system. Since this approach is limited to vehicles having air-suspension, a general application in the automotive field is not possible.
EP 1 829 714 A1 uses tire models together with pressure information from direct tire pressure sensors and the rolling radii of the wheels to calculate the load of a vehicle. This approach is not useful in applications where tire pressure and/or wheel radii are to be determined.
Further approaches include to calculate the vehicle mass based on longitudinal dynamics of a vehicle as disclosed in US 2005/0010356 A1 and vehicle mass estimation using recursive least squares (RLS) filtering as disclosed in U.S. Pat. No. 6,167,357.
Mass calculation based on longitudinal dynamics of a vehicle does not result in reliable mass estimation if, e.g., the vehicle's acceleration and/or the engine's output torque both being used in estimation are low. Using recursive least squares (RLS) filtering requires a considerable time to provide useful results (e.g. in the order of 10 minutes) and is sensitive to sudden changes of driving situations.